Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Novel Data Fusion Method and Exploration of Multiple Information Sources for
Research on low-energy nuclear reactions (LENRs) originated as the result of an electrolysis experiment that used the elements palladium (a heavy metal) and deuterium (an isotope of hydrogen). The ﬁrst modern experiment was performed by Martin Fleischmann and B. Stanley Pons at the University of Utah in early 1985. Fritz Paneth and Kurt Peters of the University of Berlin preceded Fleischmann and Pons with a similar experiment in 1926.
Data fusion is a research area that is growing rapidly due to the fact that it provides
means for combining pieces of information coming from different sources/sensors, resulting
in ameliorated overall system performance (improved decision making, increased detection
capabilities, diminished number of false alarms, improved reliability in various situations at
hand) with respect to separate sensors/sources.
The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods
Image fusion technology has successfully contributed to various fields such as medical diagnosis and navigation, surveillance systems, remote sensing, digital cameras, military applications, computer vision, etc. Image fusion aims to generate a fused single image which contains more precise reliable visualization of the objects than any source image of them. This book presents various recent advances in research and development in the field of image fusion. It has been created through the diligence and creativity of some of the most accomplished experts in various fields....
The idea of this book on Sensor fusion and its Applications comes as a response to the immense
interest and strong activities in the field of sensor fusion. Sensor fusion represents a topic of
interest from both theoretical and practical perspectives.
The technology of sensor fusion combines pieces of information coming from different
sources/sensors, resulting in an enhanced overall system performance with respect to
We present a method to automatically generate a concise s u m m a r y by identifying and synthesizing similar elements across related text from a set of multiple documents. Our approach is unique in its usage of language generation to reformulate the wording of the summary. Information overload has created an acute need for summarization. Typically, the same information is described by many different online documents.
In this paper, we examine the task of extracting a set of biographic facts about target individuals from a collection of Web pages. We automatically annotate training text with positive and negative examples of fact extractions and train Rote, Na¨ve Bayes, ı and Conditional Random Field extraction models for fact extraction from individual Web pages. We then propose and evaluate methods for fusing the extracted information across documents to return a consensus answer.
Sensor Fusion - Foundation and Applications comprehensively covers the foundation and applications of sensor fusion. This book provides some novel ideas, theories, and solutions related to the research areas in the field of sensor fusion. The book explores some of the latest practices and research works in the area of sensor fusion. The book contains chapters with different methods of sensor fusion for different engineering as well as non-engineering applications.
Using a variety of methods developed in the literature (in particular, the theory of weak Hopf algebras), we prove a number of general results about fusion categories in characteristic zero. We show that the global dimension of a fusion category is always positive, and that the S-matrix of any (not necessarily hermitian) modular category is unitary. We also show that the category of module functors between two module categories over a fusion category is semisimple, and that fusion categories and tensor functors between them are undeformable (generalized Ocneanu rigidity).
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Colour Image Segmentation Using Homogeneity Method and Data Fusion Technique
The structure and membrane interaction of the internal
fusion peptide (IFP) fragment of the avian sarcoma and
leucosis virus (ASLV) envelope glycoprotein was studied by
an array of biophysical methods. The peptide was found to
induce lipidmixing of vesicles more strongly than the fusion
peptide derived from the N-terminal fusion peptide of
influenza virus (HA2-FP). It was observed that the helical
structure was enhanced in association with the model
membranes, particularly in the N-terminal portion of the
In this chapter, the analytical embedded atom method and calculating Gibbs free energy
method are introduced briefly. Combining these methods with molecular dynamic and
Monte Carlo techniques, thermodynamics of nano-silver and alloy particles have been
Multimodal dialogue systems allow users to input information in multiple modalities. These systems can handle simultaneous or sequential composite multimodal input. Different coordination schemes require such systems to capture, collect and integrate user input in different modalities, and then respond to a joint interpretation. We performed a study to understand the variability of input in multimodal dialogue systems and to evaluate methods to perform the collection of input information.